The present invention relates generally to the field of medical diagnostic systems, such as imaging systems. More particularly, the invention relates to an apparatus and technique for multi-frame image reconstruction in a CT fluoroscopic system.
In at least one known CT system configuration, an x-ray source projects a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system and generally referred to as the "imaging plane". The x-ray beam passes through the object being imaged, such as a patient. The beam, after being attenuated by the object, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is dependent upon the attenuation of the x-ray beam by the object. Each detector element of the array produces a separate electrical signal that is a measurement of the beam attenuation at the detector location. The attenuation measurements from all the detectors are acquired separately to produce an attenuation profile.
In known third generation CT systems, the x-ray source and the detector array are rotated with a gantry within the imaging plane and around the object to be imaged so that the angle at which the x-ray beam intersects the object constantly changes. A group of x-ray attenuation measurements, i.e., projection data, from the detector array at one gantry angle is referred to as a "view". A "scan" of the object comprises a set of views made at different gantry angles, or view angles, during one revolution of the x-ray source and detector. In an axial scan, the projection data is processed to construct an image that corresponds to a two dimensional slice taken through the object. One method for reconstructing an image from a set of projection data is referred to in the art as the filtered back projection technique. This process converts the attenuation measurements from a scan into integers called "CT numbers" or "Hounsfield units", which are used to control the brightness of a corresponding pixel on a cathode ray tube display.
Certain reconstruction process steps are known to produce noise structures in an image. For example, during a "cine" scan, i.e., a scan in which the patient remains stationary while the data for the prescribed number of slices is acquired, underscan weighting ("USW") is employed to reduce motion artifacts that result when patient anatomy moves during the scan. Underscan weighting algorithms typically weight the collected data as a function of view angle and detector channel index. Specifically, prior to filtered back projection, the data is weighted according to a underscan weighting factor, which is a function of both the view angle and detector angle. Particularly, projection data is first filtered, then weighted, and subsequently backprojected to generate each image.
To reduce the total scan time, a "helical" scan may be performed. To perform a "helical" scan, the patient is moved while the data for the prescribed number of slices is acquired. Such a system generates a single helix from a one fan beam helical scan. The helix mapped out by the fan beam yields projection data from which images in each prescribed slice may be reconstructed.
Reconstruction algorithms for helical scanning typically use helical weighting ("HW") algorithms which weight the collected data as a function of view angle and detector channel index. Specifically, prior to filtered back projection, the data is weighted according to a helical weighting factor, which is a function of both the view angle and detector angle. As with underscan weighting, in a HW algorithm, projection data is filtered, weighted, and backprojected to generate each image.
In a cine scan context and a helical scan context, the same projection data is repeatedly filtered, weighted, and backprojected even though it is continually assigned the same weight. For example, projection data P.sub.1 may be weighted w.sub.1 to generate a first image I.sub.1, and also weighted w.sub.2 to generate a second image I.sub.2. However, second image I.sub.2 cannot be generated without re-filtering, re-weighting and re-backprojecting projection data P.sub.1. The underscan weighting algorithms and the helical weighting algorithms both require each image I.sub.1 and I.sub.2 to be independently generated from projection data P.sub.1. Therefore, significant computational redundancy occurs with both helical weighting algorithms and underscan weighting algorithms.
Reconstruction techniques for improving certain aspects of image generation are known. For example, overscan weighting is employed to decrease computational redundancy associated with reconstructing overlapping images with projection data. Particularly, in overscan weighting, the collected projection data is weighted only as a function of view angle. Therefore, while not completely eliminating computational redundancy, overscan weighting reduces the computations necessary for image reconstruction. Moreover, overscan weighting is known to reduce motion artifacts that result when patient anatomy moves during a 360 degree CT scan. Patient motion causes views at the beginning and ending projections to be inconsistent and discontinuous. However, while overscan weighting is successful in reducing some motion artifacts, overscan weighting is not as effective as, for example, other helical weighting algorithms. Therefore, the overscan weighting is often precluded during helical scans.
In CT fluoroscopic systems ("CT Fluoro"), it is known to generate sequential frames of images. A frame, like a view, corresponds to a two dimensional slice taken through the imaged object. Particularly, projection data is processed to construct an image frame of the object. Typically, projection data is not weighted so that the frame rate may be increased. However, non-weighted projection data is known to produce noticeable shading and streaking in generated images. To reduce such shading and streaking, helical weighting algorithms may be used to weight the projection data corresponding to each frame. However, the more often projection data is filtered, weighted and backprojected, the slower the frame rate. The frame rate is thus limited to the computational capabilities of the CT Fluoro system.
It would be desirable, of course, to decrease computational redundancy in helical scan image reconstruction. It also would be desirable to facilitate altering the number of views per frame and offer reasonable trade-offs between views per frame and frame rate in CT fluoroscopic helical image reconstruction.
Solutions to the problems described above have not heretofore included significant remote capabilities. Thus, there is a need for a medical diagnostic system which provides for the advantages of remote services and addresses the problems above. For example, it would be desirable to provide remote services to such medical diagnostic systems. In particular, there is a need for remote upgrades, remote diagnostics, remote servicing, remote viewing, remote file storage, remote control, and remote adjustments to the segmentation algorithm or other system parameters and functions. Furthermore, remote services may provide for contractual arrangements, such as, per use licenses which lease the medical diagnostic equipment based on use. Additionally, remove services may also include expert on-line assistance for image scanning techniques, image analysis, pathology detection, imaging unit maintenance, and other expert-aided operations.